Cloud Engineering

Job Description

Job Summary:

We are seeking a Senior Cloud Engineering Expert with the ability to operate across domains, including engineering processes, methods, toolchains, verification & validation (V&V), and virtualization.

This role goes beyond traditional cloud engineering and requires a strong capability to design and enable scalable, cloud-based ecosystems that support development, testing, simulation, and validation across diverse engineering domains. The candidate will act as a key enabler for digital transformation, driving standardization, automation, and adoption of modern tools and practices.

Key Responsibilities:

• Architect and manage scalable, secure, and flexible cloud platforms (Azure/AWS/GCP) to support multi-domain engineering needs.
• Design and implement cloud-based CI/CD pipelines integrating development, testing, and validation workflows.
• Enable end-to-end automation across build, test, verification, validation, and deployment processes.
• Define and standardize engineering processes, methods, and toolchains across teams.
• Establish cloud-based Verification & Validation (V&V) frameworks, including test automation, simulation, and traceability.
• Lead virtualization and containerization strategies to enable reproducible and scalable environments.
• Integrate diverse tools (ALM, DevOps, testing, simulation) into unified cloud-based ecosystems.
• Ensure best practices in cloud security, compliance, cost optimization, and observability.
• Support digital engineering initiatives such as model-based development and virtual validation environments.
• Provide technical leadership, mentoring, and guidance across teams and domains.
• Continuously evaluate and adopt emerging cloud technologies and tools.

Required Skills:

• 6–10 years of strong hands-on experience in Cloud Engineering, DevOps, or Platform Engineering roles.
• Strong expertise in at least one major cloud platform (Azure, AWS, or GCP). Should be able to work on any similar company specific platform.
• Mandatory Experience in large-scale or multi-tenant cloud environments.
• Proven experience in designing CI/CD pipelines and DevOps workflows.
• Strong understanding of engineering processes, methods, and toolchain integration.
• Experience in Verification & Validation (V&V), including test automation and validation strategies.
• Proficiency in scripting and automation (Python, Bash, PowerShell).
• Hands-on experience with containerization and virtualization technologies.
• Solid understanding of Linux/Unix environments and system troubleshooting.
• Strong problem-solving and cross-domain collaboration skills.

Preferred Skills:

• Familiarity with standards such as ISO 26262, ASPICE
• Exposure to AI/ML tools for automation, testing, or operations (AIOps).

Tools & Technologies (Expected Exposure):

Cloud Platforms:

• Microsoft Azure, AWS, Google Cloud Platform

CI/CD & DevOps:

• GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps

Infrastructure as Code & Automation:

• Terraform, Pulumi, Bicep, ARM Templates, AWS CloudFormation
• Ansible, Chef

Containerization & Orchestration:

• Docker, Kubernetes (AKS, EKS, GKE), OpenShift

Virtualization & Environment Management:

• VMware, Hyper-V, VirtualBox, KVM
• Vagrant

Verification & Validation / Testing:

• Selenium, Cypress, Playwright
• Robot Framework, pytest, JUnit
• Postman, REST Assured
• MATLAB/Simulink (for simulation use cases)
• dSPACE, Vector tools (CANoe/CANalyzer) – where applicable

Observability & Monitoring:

• Prometheus, Grafana, ELK Stack, Loki
• Azure Monitor, AWS CloudWatch, GCP Operations Suite

Security & DevSecOps:

• HashiCorp Vault, Azure Key Vault, AWS Secrets Manager
• Snyk, Trivy, SonarQube, OWASP ZAP

Collaboration & ALM Tools:

• Jira, Confluence, Polarion, Azure Boards
• Git (GitHub, GitLab, Bitbucket)

Emerging & Advanced:

• AI-assisted DevOps tools (GitHub Copilot, Azure AI, Vertex AI)
• Cloud-based simulation tools

Qualifications

B.E/ B.Tech

Additional Information

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